GitLab

This fixes a bug where equal edge descriptors would be considered
unequal. Additionally, now Vertex and Edges can be ordered (via >, <,
>=, <=).

The new format fully supports all property map types present in
graph-tool and should be much faster and produce smaller files than the
other text-based formats.

Dumping boost::adjacency_list<> improves memory usage by a factor of
two, and also slightly improves performance in some cases.

This fixes the edge invalidation check, when either the source of the
target vertex is removed.

This also makes all Edge classes inherit from the same base class of the
same name.

This fixes tickets #94 and #95

This works around a regression introduced in boost 1.48, relating to the
edge descriptors of reversed graphs.

See: https://svn.boost.org/trac/boost/ticket/6391

Now properties can be copied from vertices which are not identical
(e.g. from unfiltered to filtered graphs, etc). This fixes a problem
with graph copying and pruning, where the properties were not correclty
copied.

This implements a GraphView class which allows for convenient,
independent filtering graphs.

Now an explicit conversion to a compatible python type is attempted if
the value being set in a property map cannot be converted directly to a
C++ type.

This also fixes a bug with vector-valued property maps.

This fixes a crash when a "valid" copy of an invalid edge descriptor is
removed from the graph. Now the invalidity of the descriptor is detected
and exposed.

This fixes an obvious problem, where the graph gets deleted, and the
descriptors are still lying around. Usage of orphaned descriptors will
now just raise a ValueError.

The __repr__ function of Edge, Vertex, and PropertyMap now give
something more informative about each object.

This is a large commit which replaces lambda::bind with boost::bind in
most parts of the code. This improves compilation time, and slightly
decreases compilation memory usage in some cases.

This also includes convenience property map checks.

No longer only thrown GraphError upon any error, but instead throw
specific exceptions which are more meaninful and are mapped to standard
python exceptions, such as IOError, ValueError and RuntimeError.

The following conversions are now possible: int(v) and tuple(e), where v
and e are Vertex and Edge instances, respectively.

Thins changes the graph filtering code slightly to wrap graph types with
GraphWrap, which automatically updates the edge index list when edges
are removed and added to the graph.

This also changes how graphs are passed to algorithms, which is now by
reference instead of pointer. (hence this touches lots of code, but
changes are trivial)

This includes the missing function declarations for edge and graph
properties.

Property maps of value type "string" do not return an array, since the
numpy string and std::string are different things.

This includes a new vector property map type (fast_vector_property_map)
which has optional disabling of bounds checking, through its associate
map type (unchecked_fast_vector_property_map). This should improve
performance on algorithms which depend on tight loops which access
property maps.

Bounds checking is only disabled locally just before the algorithms run,
and proper care is taken for bounds checking _beforehand_. The property
maps exposed to python still have internal bounds checking.

A property map object has now a get_array() member which returns an internally
owned array pointing to the property values.

This makes operations on graphs more flexible in some circumstances.

This commit removes the internal property maps from the GraphInterface
class, and makes all property maps external by default. The internal
property maps were moved to the python layer.

This fixes the representation of property maps which don't have a
value type included in the value_types list, such as index properties.

The whole histogram code has been redone, and the code has been
simplified. The three-point vertex-edge-vertex correlation has been
scrapped, since it's not frequently used, and would make compilation
even more expensive.

This also adds some missing files to the generation routine.

Now graphml files properly contain all the supported value types, which
are all perfectly preserved when read (floating point data is now saved
in hexadecimal format). Several other improvements were made, such as
the ability to read and write to python file-like objects.

It is also now possible to have arbitrary python object properties, and
store them persistently (which is done internally with the pickling
interface).

vector<bool> was totally abolished, since its implementation is quite
broken. See: http://www.gotw.ca/publications/N1211.pdf and
http://www.gotw.ca/publications/N1185.pdf Now a uint8_t (aka. char) is
used in graph properties instead of a bool.

Graph types can now be fully pickled (this may not be feasible
memory-wise if the graph is too large, since the whole XML
representation is dumped to a string before it is saved on disc).

This commit splits libraph_tool into different libraries:
 
   - libgraph_tool_core
   - libgraph_tool_clustering (*)
   - libgraph_tool_community (*)
   - libgraph_tool_correlations (*)
   - libgraph_tool_distance (*)
   - libgraph_tool_generation (*)
   - libgraph_tool_layout (*)
   - libgraph_tool_misc (*)
   - libgraph_tool_stats (*)

It also adds the python sub-module 'test', which provides extensive unit
testing of the core functionality. The core library is fully functional
and all test pass successfully.

(*) -> module needs to be ported to new refactoring, and does not yet build

This is a huge commit which completely refactors the metaprogramming
engine which generates and selects (at run time) the graph view type and
the desired algorithm implementation (template instantiation) that runs
on it.

Things are laid out now as following. There exists a main underlying
graph type (GraphInterface::multigraph_t) and several other template
classes that mask it some way or another, in a hierarchic fashion:

     multigraph_t -> filtered_graph (edges only, vertices only, both)
         |                               |           |           |
         |                               |           |           |
         |-------(reversed_graph)--------|-----------|-----------|
         |                               |           |           |
         \------(UndirectedAdaptor)------------------------------/

The filtered_graph filters out edges and/or vertices from the graph
based on some scalar boolean property. The reversed_graph reversed the
direction of the edges and, finally, the UndirectedAdaptor treats the
original directed graphs as undirected, transversing the in- and
out-edges of each vertex indifferently. Thus, the total number of graph
view types is 12. (The option --disable-graph-filtering can be passed to
the configure script, which will disable graph filtering altogether and
bring the total number down to 3, to reduce compile time and memory
usage)

In general, some specific algorithm, implemented as a template function
object, needs to be instantiated for each of those types. Furthermore,
the algorithm may also depend on other types, such as specific
property_maps. Thus, the following scheme is used:

    struct my_algorithm // algorithm to be implemented
    {
        template <class Graph, class PropertyMap>
        void operator()(Graph *g, PropertyMap p, double& result) const
        {
            // ...
        }
    };

    // in order for the above code to be instantiated at compile time
    // and selected at run time, the run_action template function object
    // is used from a member function of the GraphInterface class:

    double GraphInterface::MyAlgorithm(string prop_name)
    {
        double result;
        boost::any vprop = prop(property, _vertex_index, _properties);
        run_action<>()(*this, bind<void>(my_algorithm(), _1, _2,
                                         var(result)),
                       vertex_scalar_properties())(vprop);
        return result;
    }

The whole code was changed to reflect this scheme, but now things are
more centralized and less ad-hoc code needed to be
written. Unfortunately, due to GCC's high memory usage during template
instantiations, some of the code (namely all the degree correlation
things) had to be split in multiple compilation units... Maybe this will
change in the future if GCC gets optimized.

This commit also touches other parts of code. More specifically, the way
filtering gets done is very different. Now we only filter on boolean
properties, and with the above scheme, the desired implementation runs
with the correct chosen type, and no implicit type conversions should
ever happen, which would have a bad impact on performance.